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This paper presents a simple recipe to train state-of-the-art multilingual Grammatical Error Correction (GEC) models.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019 · 1910
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Stronger baselines for grammatical error correction using pretrained encoder-decoder model
Satoru Katsumata and Mamoru Komachi. 2020 · 2005
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A new dataset and method for automatically grading ESOL texts
Helen Yannakoudakis, Ted Briscoe, and Ben Medlock. 2011 · 2011
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Exploring grammatical error correction with not-so-crummy machine translation
Nitin Madnani, Joel Tetreault, and Martin Chodorow. 2012 · 2012
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The wiked error corpus: A corpus of corrective wikipedia edits and its application to grammatical error correction
Roman Grundkiewicz and Marcin Junczys-Dowmunt. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Using Wikipedia edits in low resource grammatical error correction
Adriane Boyd. 2018 · 2018
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Parallel iterative edit models for local sequence transduction
Abhijeet Awasthi, Sunita Sarawagi, Rasna Goyal, Sabyasachi Ghosh, and Vihari Piratla. 2019 · 2019
Cited alongside, same era.
The BEA-2019 shared task on grammatical error correction
Christopher Bryant, Mariano Felice, Øistein E. Andersen, and Ted Briscoe. 2019a · 2019
Cited alongside, same era.
The BEA-2019 shared task on grammatical error correction
Christopher Bryant, Mariano Felice, Øistein E. Andersen, and Ted Briscoe. 2019b · 2019
Cited alongside, same era.
Kermit: Generative insertion-based modeling for sequences
William Chan, Nikita Kitaev, Kelvin Guu, Mitchell Stern, and Jakob Uszkoreit. 2019 · 2019
Cited alongside, same era.
Neural grammatical error correction systems with unsupervised pre-training on synthetic data
Roman Grundkiewicz, Marcin Junczys-Dowmunt, and Kenneth Heafield. 2019 · 2019
Cited alongside, same era.
Grammar error correction in morphologically rich languages: The case of Russian
Alla Rozovskaya and Dan Roth. 2019 · 2019
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MASS: masked sequence to sequence pre-training for language generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu. 2019 · 2019
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Data weighted training strategies for grammatical error correction
Jared Lichtarge, Chris Alberti, and Shankar Kumar. 2020 · 2020
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FELIX: Flexible text editing through tagging and insertion
Jonathan Mallinson, Aliaksei Severyn, Eric Malmi, and Guillermo Garrido. 2020 · 2020
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Corpora generation for grammatical error correction
Jared Lichtarge, Chris Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar, and Simon Tong. 2019 · 2019
Cited alongside, same era.
Encode, tag, realize: High-precision text editing
Eric Malmi, Sebastian Krause, Sascha Rothe, Daniil Mirylenka, and Aliaksei Severyn. 2019 · 2019
Cited alongside, same era.
Grammatical error correction in low-resource scenarios
Jakub Náplava and Milan Straka. 2019 · 2019
Cited alongside, same era.
GECToR – grammatical error correction: Tag, not rewrite
Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub, and Oleksandr Skurzhanskyi. 2020 · 2020
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Leveraging pre-trained checkpoints for sequence generation tasks
Sascha Rothe, Shashi Narayan, and Aliaksei Severyn. 2020 · 2020
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mt5: A massively multilingual pre-trained text-to-text transformer
Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel. 2020 · 2020
Later among the works it cites.